We talk a lot about AI that can think, AI that
can write. It gives you information. But imagine
an AI that doesn't just hand you a map to a good
coffee shop. Imagine it actually acts as your
personal driver. Exactly. No more just scrolling
through 10 search results, hoping you find what
you need. Now the AI agent, it actively checks
the hours. It verifies they sell that specific
croissant you like, figures out the parking,
and then it tells you definitively, go here.
That active multi -step thing. That's the real
game changer. Welcome to the deep dive. Today
we're exploring what feels like the critical
next step in artificial intelligence. the AI
agent. Specifically, we're diving into Perplexity
Comet, a system that seems to be transforming
passive searching into, well, active task completion.
Yeah, and just quickly, for anyone maybe new
to the term, when we say AI agent, what we mean
is pretty simple. It's an AI that follows a complex
multi -step process. It completes entire jobs
for you. It's really built to execute a workflow,
you know? OK. And we've got a lot to unpack today.
We're looking at... 10 of what seem to be the
most powerful automated helders the system offers.
We've kind of grouped them into three key areas.
First is sales and customer insight. Second,
research and content creation. And finally, automating
some of that core office operations stuff. So
let's dig into this shift first. Okay, so let's
start with the fundamental shift itself. For
years we've gotten used to things like chat GPT,
that smart brain capability, it's great AI for
thinking, for writing, explaining complex ideas,
but now we're moving to AI that has Well, the
sources call it hands and feet. They can actually
do work. Yeah, it's truly about getting rid of
the digital drudgery, you know, the old way,
constantly copying and pasting data between sites
or writing basically the same intro email over
and over. It was all manual data pushing. Right.
And the new way is automating those boring, repetitive
jobs, but without needing you to be some kind
of tech wizard or programmer. The complexity
is sort of hidden. You don't need code. You just
need to get good at giving really clear layered
commands in plain English. Mm -hmm, and you interact
with these agents in like two main ways for the
big complex stuff You know plan my whole trip
budget and itinerary use the main chat window,
but for quicker tasks things related to the web
page You're looking at right now like summarize
this or check the author That's where the assistant
sidebar comes in handy. Okay, so since this whole
idea hinges on making complexity accessible meaning
we don't need to code What's the single biggest
time saver this offers someone who isn't a programmer?
Definitely automating those repetitive data gathering
tasks and comparing stuff across multiple sites.
Saves hours weekly. Automating multi -site comparisons
and repetitive data fetching saves hours weekly.
Got it. All right, let's move into our first
group, sales. This is where these agents seem
to generate highly personalized leads and pretty
detailed market insights fast. Yeah, the first
one is the leads monitoring agent. This is designed
to automatically find potential customers showing
real purchase intent on social media. I think
Reddit, Twitter, places like that. The example
they use is great for a freelancer, like a video
editor. Instead of manually searching for hours,
you tell the agent, look on subreddits, say YouTubers,
for people posting, looking for an editor. But
here's the crucial bit, the how. How does it
filter out the noise, the tire kickers? Ah, that's
where the agentic logic kicks in. It uses these
complex, kind of nested rules. You're basically
telling the AI, if you see looking for editor,
and if they also mention budget or schedule explicitly,
then flag it. Put it on the list. It's like stacking
these little Lego blocks of data requirements,
you know? Mm -hmm. And it catches that user,
Koalunov, who offered $15 an hour and specified
a clear schedule. It's a qualified lead, just
delivered to you. Okay, so the leads agent finds
the prospect. Now the next hurdle is outreach
without sounding like, you know, generic spam.
Exactly. And that's the job for the sales prospecting
agent. It writes the sales emails. You set the
rules. Find, say, 10 family -owned restaurants
in NYC. But then you add critical steps. Like,
the email most complemented specific menu item
to show you actually looked. And maybe point
out their website looks kind of old, isn't mobile
friendly, and offer some free ideas. That personalization
makes all the difference. You've earned their
attention. Okay, and then the third agent in
this sales group is the audience research agent.
This is about finding real pain points. Oh yeah,
this one's incredibly powerful, especially if
you're building a product. Let's say you're making
a beginner guitar course. You tell the agent,
Analyze the comments under the five most popular
why I quit guitar videos on YouTube. It reads
thousands of comments to find the top five common
reasons like my fingers hurt or I'm not seeing
progress. And it pulls out the actual quotes
like direct language from users. Exactly. You
get stuff like I practice for three weeks and
I still can't change from a C to a G chord smoothly.
I feel useless. That real verified language.
That's gold dust for development. It really is.
Honestly. I still wrestle with prompt refinement
sometimes, trying to get that kind of specific
insight manually. It's hard. The ability to just
pull that verified quote, that raw feeling. It
makes product development so much more focused.
It's a huge advantage. So how does using those
real customer quotes from this kind of research
actually change how we design products or services?
Products address verified problems, moving beyond
just guesswork about customer needs. OK, let's
switch gears now to the second group. Research
and content. This is all about slashing that
tedious data gathering time. The live marketing
intelligence agent is a fantastic example of
just raw speed. Yeah, this takes what might have
been like a two -hour copy -paste slog and turns
it into a two -minute task. You open tabs for
four competitors, Amazon, Alibaba, whoever, and
you tell the agent to scan them all at once.
It just pulls out their holiday sales info, the
exact discounts, the main call to action words
they're using. bang, instantly organized in a
table. That kind of speed for competitive analysis.
It's a game changer. It really is. But scanning
foresight simultaneously, doesn't that risk missing
some important context? Or maybe nuances in how
they present the sale? That's a really short
point. What's interesting is how it works. The
agent is only looking for a few specific things
you told it to find the discount percentage,
the dates, those CTA words. It minimizes the
risk of missing broader context by keeping its
focus super narrow just on the data points you
asked for. It's like laser -focused execution.
Okay, that makes sense. Next up is the research
agent. Digital declutterer you called it if your
browser is a mess with 30 tabs open Yeah, this
agent groups them into organized workspaces like
the California trip example in the source It
makes folders hotels flights food, but then it
goes further It actually reads the content of
those hotel tabs and summarizes say the top three
options that have both the best reviews and a
swimming pool You know the Ritz -Carlton Half
Moon Bay 4 .7 stars heated outdoor pool That
level of synthesis saves so much time. And moving
to the synthesizer agent, this is where we get
into that permanent recurring automation. You
set it up once and it just runs. Pretty much.
You schedule a task every Monday, 8 -6 -0 AM
sharp, find the five most important news stories
about EV batteries from the last week, summarize
them, add them to my Notion database. Done. I'm
just picturing. Ditching that Sunday night scramble
to catch up on industry news that scheduled automation
isn't just powerful It feels like getting time
back. Whoa Imagine scaling that that weekly knowledge
base just builds itself forever like a second
brain But with zero daily effort from you totally
and the last one in this group the content brief
agent Helps make sure your articles are actually
competitive So if you're writing about say how
to care for a ZZ plan the agent looks at the
top search results It identifies the five most
common sub -questions people ask. And it might
flag a unique angle others are missing, like
leaf care and aesthetic maintenance. It even
makes sure you include a common mistakes section,
because over -watering is the number one killer
for those plants. It's like having a research
assistant specifically for content strategy.
Yeah. OK. Thinking about that scheduled database
update, what's the most important practical benefit
there? You build a personal knowledge library
with zero daily maintenance effort. Mid -roll
sponsor read. All right, let's shift gears one
last time. Group three, internal processes, office
work, operation stuff. First up is the conversion
optimization agent. This one basically acts like
a secret shopper for your own website. Right,
you give it a document, maybe purchase test steps,
find the leather notebook, add it to the cart,
try using discount code test10 at checkout, and
it just follows those steps, exactly. Like a
real user would. Yeah, exactly. And then it reports
back on the friction points. It lists, say, the
top five problems it encountered that might be
cost to you sales without you even realizing
it. Like finding that subtle bug where the discount
code doesn't work on the mobile checkout screen,
maybe? That kind of thing? Precisely those kinds
of hidden snacks. Then there's the talent sourcing
agent, which sounds incredible for hiring. Hiring
takes so much time. Filtering through candidates.
Tell me about it. Yeah. But this agent handles
the heavy lifting on the filtering. You can set
really strict rules like, find me Facebook ads
specialists on Upwork who must be top rated,
must have earned over $10k, must have e -commerce
experience, and must have five -star reviews
that specifically mention the phrase conversion
rate. Wow. So you skip scrolling through hundreds
of profiles that say they're experts, but lack
those specific verifiable metrics the agent is
checking for. It just gives you a short, high
quality list ready for actual interviews. It's
huge. Huge time saver. But honestly, the kind
of crowning achievement in this operations group,
I think, is the executive assistant agent. OK.
Tell me about this one. It connects your calendar,
docs, and the web. Yeah. So you ask it, prep
me for tomorrow's meetings if you have external
meetings scheduled. It goes out and researches
the latest news on those companies, finds out,
OK, Stripe is making big moves into stable coins
right now. And for each person you're meeting,
it summarizes their latest LinkedIn activity
or profile updates. And then crucially, it suggests
maybe two smart relevant questions you could
ask based on that fresh news it found. So you
walk into every meeting looking incredibly prepared,
leveraging really specific, up -to -the -minute
context. Exactly. You look like the most informed
person in the room, basically. Thinking about
competitive advantage here, if you're short on
prep time, which of these agents gives you the
biggest professional edge, do you think? Good
question. I'd say the executive assistant. It
ensures you're fully informed and professional
for every critical meeting. Okay, let's just
quickly recap the core difference again between
these agentic AIs and something like chat GPT.
Chat GPT is like that brilliant brain in a room.
It's a great writer, a teacher, fantastic at
explaining things. But its limitation, fundamentally,
is that it can't really act in your world natively.
It can't check your actual email inbox or save
files directly without some pretty complex workarounds
or integrations. Right. Whereas perplexity comment
and agents like it. are designed more like an
assistant with, well, hands and feet. It's built
from the ground up to do research and complete
tasks. Its strength is connecting directly to
your tools, your browser, maybe your email eventually,
your documents, to finish those multi -step jobs
without you having to manually shuttle data around.
You should absolutely be using both kinds of
tools, really, for what they're best at. Definitely.
Now, a really important point, privacy. For any
AI helper to be genuinely useful like this, it
needs context, right? It needs to be able to
read your browser tabs, maybe look at your documents,
understand your calendar, and that means we have
to be mindful about the data it sees. Absolutely
critical. The first, easy step. Go into the perplexity
settings. Turn off options like send your data
to improve the product, basic hygiene, but the
best practice, honestly, separation. Use a completely
new Google account or maybe even a separate web
browser profile. only for your work tasks with
perplexity. That keeps your personal emails,
your banking stuff, all that sensitive data completely
isolated from the agent's workspace. So what's
the essential trade -off we're making here when
we use a tool that needs our context to be this
helpful? We trade a degree of privacy for increased
automation and powerful task completion. Hashtag,
hashtag, outro. So the big idea today seems really
clear. The future of AI isn't just about conversation.
It's about agentic action. These are tools being
built specifically to do the work, to handle
those complex multi -step jobs that used to eat
up so much of our time. Yeah. And my practical
advice, don't try to tackle all 10 of these agents
at once. That's overwhelming. Just pick the single
most boring or the most repetitive task in your
job right now. Is it finding qualified leads?
Is it organizing research every week? Start.
there, use the detailed prompt examples we talked
about as you're jumping off point, just automate
that one tedious thing first. It really feels
like a compelling glimpse into the future. I
mean, if AI agents can now audit your website,
find your talent, prep you for meetings, all
with minimal human effort, how long until purely
human -led single -step tasks start to look inefficient
in, well, almost every professional field? It's
certainly something powerful to think about until
our next deep dive. Indeed it is. We'll see you
next time.